A Survey on Biometrics based Key Authentication using Neural Network

The conventional method for user authentication is a password known to the user only. There is no security in the use of passwords if the password is known to an imposter and also it can be forgotten. So it is necessary to develop a better security system. Hence, to improve the user authentication passwords are replaced with biometric identification of the user. Thus usage of biometrics in authentication system becomes a vital technique. Biometric scheme are being widely employed because of their security merits over the earlier authentication system based on records that can be easily lost, guessed or forged. This is because the biometrics is unique for every individual and is complex than passwords. Commonly used biometrics is fingerprint, iris, retina, face, hand geometry, palm, etc. The two issues to be considered for user authentication system are recognition of the authorized user and rejection of the impostor. So a better classifier is necessary to perform this task. Some of the widely used classifier is based on fuzzy logic, neural network, etc. Among those, neural network can be efficient in classification. This survey provides various biometrics based authentication system based on neural network

A Survey on Biometrics based Key Authentication using Neural Network

The conventional method for user authentication is a password known to the user only. There is no security in the use of passwords if the password is known to an imposter and also it can be forgotten. So it is necessary to develop a better security system. Hence, to improve the user authentication passwords are replaced with biometric identification of the user. Thus usage of biometrics in authentication system becomes a vital technique. Biometric scheme are being widely employed because of their security merits over the earlier authentication system based on records that can be easily lost, guessed or forged. This is because the biometrics is unique for every individual and is complex than passwords. Commonly used biometrics is fingerprint, iris, retina, face, hand geometry, palm, etc. The two issues to be considered for user authentication system are recognition of the authorized user and rejection of the impostor. So a better classifier is necessary to perform this task. Some of the widely used classifier is based on fuzzy logic, neural network, etc. Among those, neural network can be efficient in classification. This survey provides various biometrics based authentication system based on neural network

Performance of keystroke biometrics authentication system using Multilayer Perceptron neural network (MLP NN)

The use of computer has increased rapidly as well as the use of internet applications such as e-commerce, online banking services, webmail, and blogs. All internet applications require a password authentication scheme to make sure only the genuine individual can login to the application. Passwords and personal identification numbers (PIN) have traditionally been used to access such applications. However, it is easy for unauthorized persons to access these systems without detection. This paper addresses the issue of enhancing such systems using keystroke biometrics as a translucent level of user authentication. The paper focuses on using the time interval (key down-down) between keystrokes as a feature of individuals' typing patterns to recognize authentic users and reject imposters. A Multilayer Perceptron (MLP) neural network with a Back Propagation (BP) learning algorithm is used to train and validate the features